A 6-month deployment of instrumentation from April to October 2012 in 90 m water depth near the outer edge of the mid-shelf mud belt in southern Monterey Bay, California, reveals the importance regional upwelling on water column density structure, potentially accounting for the majority of the variability in internal tidal energy flux across the shelf. Observations consisted of time-series measurements of water-column currents, temperature and salinity, and near-bed currents and suspended matter. The internal tide accounted for 15–25% of the water-column current variance and the barotropic tide accounted for up to 35%. The subtidal flow showed remarkably little shear and was dominated by the 7–14 day band, which is associated with relaxations in the dominant equatorward winds typical of coastal California in the spring and summer. Upwelling and relaxation events resulted in strong near-bed flows and accounted for almost half of the current stress on the seafloor (not accounting for wave orbital velocities), and may have driven along-shelf geostrophic flow during steady state conditions. Several elevated suspended particulate matter (SPM) events occurred within 3 m of the bed and were generally associated with higher, long-period surface waves. However, these peaks in SPM did not coincide with the predicted resuspension events from the modeled combined wave–current shear stress, indicating that the observed SPM at our site was most likely resuspended elsewhere and advected along-isobath. Sediment flux was almost equal in magnitude in the alongshore and cross-shore directions. Instances of wave–current shear stress that exceeded the threshold of resuspension for the silty-clays common at these water depths only occurred when near-bed orbital velocities due to long-period surface waves coincided with vigorous near-bed currents associated with the internal tide or upwelling/relaxation events. Thus upwelling/relaxation dynamics are primarily responsible for variability in the internal tide, as well as transport of near-bottom sediment in the mid-self mud belt during the relatively quiescent summer months.
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We measured plant-available phosphorus (Mehlich-3: MeP) in soil samples, and assessed the vascular plant community and habitat degradation at 27 emergent and 13 forested wetlands in Ohio, USA. We tested two hypotheses: (1) that an index of vegetation biological integrity based on floristic quality was lower in wetlands with higher concentrations of MeP in the soil, and (2) that higher concentrations of MeP occurred in wetlands with more habitat degradation (i.e., lower quality), as estimated by a rapid assessment method. Hypothesis (1) was supported for emergent, but not for forested wetlands. Hypothesis (2) was marginally supported (P = 0.09) for emergent, but not supported for forested wetlands. The results indicate that the effect of concentration of phosphorus in wetland soils and the quality of plant species assemblages in wetlands is more complex than shown in site-specific studies and may depend in part on degree of disturbance in the surrounding watershed and dominant wetland vegetation type. Woody plants in forested wetlands are typically longer lived than herbaceous species in the understory and emergent wetlands, and may persist despite high inputs of phosphorus. Further, the forested wetlands were typically surrounded by a wide band of forest vegetation, which may provide a barrier against sedimentation and the associated phosphorus inputs to the wetland interior. Our results indicate that inferences about soil nutrient conditions made from rapid assessment methods for assessing wetland habitat condition may not be reliable.
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Brian","contributorId":52061,"corporation":false,"usgs":true,"family":"Gara","given":"Brian","affiliations":[],"preferred":false,"id":623211,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Monteith, Steve","contributorId":167706,"corporation":false,"usgs":false,"family":"Monteith","given":"Steve","email":"","affiliations":[{"id":5108,"text":"U.S. Department of Agriculture Forest Service, Rocky Mountain Research Station, Missoula, Montana 59","active":true,"usgs":false}],"preferred":false,"id":623212,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70168820,"text":"fs20163010 - 2016 - Groundwater contaminant science activities of the U.S. Geological Survey in New England","interactions":[],"lastModifiedDate":"2017-06-30T10:06:13","indexId":"fs20163010","displayToPublicDate":"2016-03-23T11:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3010","title":"Groundwater contaminant science activities of the U.S. Geological Survey in New England","docAbstract":"Aquifers in New England provide water for human needs and natural ecosystems. In some areas, however, aquifers have been degraded by contaminants from geologic and human sources. In recent decades, the U.S. Geological Survey has been a leader in describing contaminant occurrence in the bedrock and surficial aquifers of New England. In cooperation with Federal, State, and local agencies, the U.S. Geological Survey has also studied the vulnerability of groundwater to contaminants, the factors affecting the geographic distribution of contaminants, and the geochemical processes controlling contaminant transport and fate. This fact sheet describes some of the major science needs in the region related to groundwater contaminants and highlights recent U.S. Geological Survey studies that provide a foundation for future investigations.
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U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
The U.S. Geological Survey (USGS) has a long history of working with the Federal Highway Administration (FHWA) and State transportation agencies to provide data and information to address various issues related to water resources and the Nation’s transportation infrastructure. These issues include the following:
\n• Streamgaging data networks
• Flow frequencies and flow statistics
• Water-quality investigations
• Bridge scour and sediment transport
• Hydrologic and hydraulic flood modeling
In New England, the USGS is conducting investigations to improve flood flow estimation techniques, to define channel characteristics at bankfull discharge, and to document storm tide as a result of major coastal storms. Current locally focused investigations include examination of flow frequency in rural, urban, and small watersheds; documentation of extreme inland floods along with flood-frequency updates; examination of the effects of roadway blasting on groundwater quality; and determinations of the effects of road salting on the quality of runoff and receiving waters.
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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
The U.S. Geological Survey (USGS) has actively pursued research in the effects of climate change on the hydrology of New England. Ongoing focus areas of climate change science activities of the USGS in New England include the following:
\n• Hydrologic climate-response data (initiating or expanding long-term hydrologic climate-response data collection networks to detect and monitor climate-related changes in hydrology)
• Relations between historical climatic and hydrologic variation (investigating historic relations between long-term climatic variation and hydrologic variation and connecting these relations to future conditions as forecasted by the Interagency Panel on Climate Change (Nakićenović and others, 2000)
• Hydrologic change on natural and human (incorporating climate change scenarios into assessments of how flows in streams or water levels in aquifers may change)
• Relations between climatic and hydrologic variation (characterizing impacts of climate change on floods and droughts, the long-term availability of water supplies for societal and natural uses in response to climate changes)
• Developing tools to forecast ecosystem change and water resources management (developing regionally consistent tools for forecasting ecosystem change and resource management)
This fact sheet presents recent climate change investigations of the USGS in New England using selected recent publications. These publications highlight the broad spectrum of expertise and commitment to understanding the relations of climate change and water resources in New England.
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\"}}]}","contact":"Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
The U.S. Geological Survey (USGS) has many ongoing and recent water-related natural hazard activities in New England that can be used to help mitigate the effects of natural hazards in cooperation with other agencies. The themes related to potential hazards and the tools and science to better understand and address them include the following:
\nErosion and landslides
• Fluvial erosion (sediment transport, bridge scour, and bankfull channel geometry characterization)
• Current and historic landslide mapping
Flood documentation and assessment
• Flood high-water marks
• Flood modeling and frequency analysis
• Flood inundation mapping
• Peak-flow regression equations
Drought documentation and assessment
• Drought frequency analysis
• Low-flow frequency and flow duration statistics
• Water use and availability during drought
Hydrologic monitoring
• Streamflow monitoring network
• Groundwater monitoring network
• Tidal monitoring network
• Snow surveys and ice jam monitoring
Tools for natural hazard assessment and mitigation
• Light detection and ranging (lidar) remote sensing technology
• StreamStats Web-based tool for streamflow statistics
• Flood inundation mapper
Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
The U.S. Geological Survey (USGS) collaborates with a variety of Federal, State, local, and tribal partners on scientific projects to provide reliable and impartial water-quality data and interpretation to resource managers, planners, stakeholders, and the general public. The themes related to surface water quality include the following:
\n• Water quality monitoring networks
• Effects of best management practices and low impact development on water quality
• Load estimation techniques and total maximum daily load assistance
• Mercury studies
• Toxics and emerging contaminants
• Eutrophication and nuisance algal blooms
Director, New England Water Science Center
U.S. Geological Survey
331 Commerce Way, Suite 2
Pembroke, NH 03275
Or visit our Web site at
http://newengland.water.usgs.gov/
Using water column temperature records collected since 1968, we analyzed the impacts of climate change on thermal properties, stability intensity, length of stratification, and deep mixing dynamics of Lake Tahoe using a modified stability index (SI). This new SI is easier to produce and is a more informative measure of deep lake stability than commonly used stability indices. The annual average SI increased at 16.62 kg/m2/decade although the summer (May–October) average SI increased at a higher rate (25.42 kg/m2/decade) during the period 1968–2014. This resulted in the lengthening of the stratification season by approximately 24 d. We simulated the lake thermal structure over a future 100 yr period using a lake hydrodynamic model driven by statistically downscaled outputs of the Geophysical Fluid Dynamics Laboratory Model (GFDL) for two different green house gas emission scenarios (the A2 in which greenhouse-gas emissions increase rapidly throughout the 21st Century, and the B1 in which emissions slow and then level off by the late 21st Century). The results suggest a continuation and intensification of the already observed trends. The length of stratification duration and the annual average lake stability are projected to increase by 38 d and 12 d and 30.25 kg/m2/decade and 8.66 kg/m2/decade, respectively for GFDLA2 and GFDLB1, respectively during 2014–2098. The consequences of this change bear the hallmarks of climate change induced lake warming and possible exacerbation of existing water quality, quantity and ecosystem changes. The developed methodology could be extended and applied to other lakes as a tool to predict changes in stratification and mixing dynamics.
","language":"English","publisher":"Wiley & Sons Ltd.","doi":"10.1002/lno.10228","usgsCitation":"Sahoo, G.B., Forrest, A.L., Schladow, S., Reuter, J.E., Coats, R., and Dettinger, M.D., 2016, Climate change impacts on lake thermal dynamics and ecosystem vulnerabilities: Limnology and Oceanography, v. 61, p. 496-507, https://doi.org/10.1002/lno.10228.","productDescription":"11 p.","startPage":"496","endPage":"507","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-057124","costCenters":[{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true}],"links":[{"id":471128,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/lno.10228","text":"Publisher Index Page"},{"id":325694,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"California, Nevada","otherGeospatial":"Lake 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E","contributorId":173178,"corporation":false,"usgs":false,"family":"Reuter","given":"J.","email":"","middleInitial":"E","affiliations":[{"id":27174,"text":"UC Davis, Tahoe Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":643558,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coats, R.","contributorId":9540,"corporation":false,"usgs":true,"family":"Coats","given":"R.","email":"","affiliations":[],"preferred":false,"id":643559,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dettinger, Michael D. 0000-0002-7509-7332 mddettin@usgs.gov","orcid":"https://orcid.org/0000-0002-7509-7332","contributorId":149896,"corporation":false,"usgs":true,"family":"Dettinger","given":"Michael","email":"mddettin@usgs.gov","middleInitial":"D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":438,"text":"National Research Program - Western Branch","active":true,"usgs":true},{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":643554,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70160548,"text":"sir20105090AA - 2016 - Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: Chapter AA in Global mineral resource assessment","interactions":[{"subject":{"id":70160548,"text":"sir20105090AA - 2016 - Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: Chapter AA in Global mineral resource assessment","indexId":"sir20105090AA","publicationYear":"2016","noYear":false,"chapter":"AA","title":"Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: Chapter AA in Global mineral resource assessment"},"predicate":"IS_PART_OF","object":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"id":1}],"isPartOf":{"id":70040436,"text":"sir20105090 - 2010 - Global mineral resource assessment","indexId":"sir20105090","publicationYear":"2010","noYear":false,"title":"Global mineral resource assessment"},"lastModifiedDate":"2016-03-23T15:14:43","indexId":"sir20105090AA","displayToPublicDate":"2016-03-23T09:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2010-5090","chapter":"AA","title":"Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: Chapter AA in Global mineral resource assessment","docAbstract":"Undiscovered potash resources in the Central Asia Salt Basin (CASB) of Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan were assessed as part of a global mineral resource assessment led by the U.S. Geological Survey. The term “potash” refers to potassium-bearing, water-soluble salts derived from evaporite basins, where seawater dried up and precipitated various salt compounds; the word for the element “potassium” is derived from potash. Potash is produced worldwide at amounts exceeding 30 million metric tons per year, mostly for use in fertilizers. The term “potash” is used by industry to refer to potassium chloride, as well as potassium in sulfate, nitrate, and oxide forms. For the purposes of this assessment, the term “potash” refers to potassium ores and minerals and potash ore grades. Resource and production values are usually expressed by industry in terms of K2O (potassium oxide) or muriate of potash (KCl, potassium chloride).
\nThe CASB hosts significant discovered potash resources and originated in an inland sea during Late Jurassic time. Seawater flowed into the CASB, mostly from its extreme northwestern margin near the modern Caspian Sea, during several evaporation episodes that deposited at least five different packages of evaporites, with virtually all potash in the second and fourth packages. In this study, the CASB was subdivided into three tracts (permissive areas) for evaluation: the Amu Darya tract in the west, the Gissar tract in the center, and the Afghan-Tajik tract in the east. The Gissar and Amu Darya tracts were quantitatively assessed, whereas the Afghan‑Tajik tract was only qualitatively assessed because of the commonly extreme depth (as deep as 7 km) of the Jurassic salt, extensive deformation, and a lack of known potash deposits.
\nTwo approaches were used to estimate amounts of undiscovered potash in the CASB. Stratabound evaporite deposits in the Amu Darya tract were evaluated using an Adaptive Geometric Estimation (AGE) approach, which estimates in-place potash volumes and tonnages. The Gissar tract was evaluated by using the AGE approach for stratabound deposits and the three-part form of assessment of Singer and Menzie (2005) for discrete halokinetic deposits. In the three-part form of assessment, numbers of undiscovered deposits were estimated and combined with grade and tonnage models to probabilistically forecast the amount of undiscovered potash. The Amu Darya tract is estimated to contain 38 billion metric tons of undiscovered potash as K2O by using the AGE approach for stratabound deposits. The hybrid stratabound-halokinetic Gissar tract is estimated to contain between 1 and 16 billion metric tons of undiscovered potash as K2O.
\nChapter 1 of this report provides an overview of the history of the CASB and summarizes evaporite potash deposition, halokinesis, and dissolution processes that have affected the current distribution of potash-bearing salt in the CASB. Chapter 2 describes the Gissar tract, an uplifted region that contains a mix of stratabound and halokinetic potash deposits and all of the discovered and exploited potash deposits of the CASB. Chapter 3 describes the Amu Darya tract, where evaporite deposits remain flat-lying and undeformed since their original deposition. Chapter 4 describes the highly deformed and compressed Afghan-Tajik tract and what is known of the deeply-buried Jurassic salt. Chapter 5 describes the spatial databases included with this report, which contain a collection of CASB potash information. Appendixes A and B summarize descriptive models for stratabound and halokinetic potash-bearing salt deposits, respectively. Appendix C summarizes the AGE method used to evaluate the Gissar and Amu Darya tracts. Appendixes D and E contain grade and thickness data for the Gissar and Amu Darya tracts. Appendix F provides the SYSTAT script used to estimate undiscovered K2 O in a CASB tract. Appendix G provides a potash glossary, and appendix H provides biographies of assessment participants.
","largerWorkType":{"id":18,"text":"Report"},"largerWorkTitle":"Global mineral resource assessment (Scientific Investigations Report 2010-5090)","largerWorkSubtype":{"id":5,"text":"USGS Numbered Series"},"language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20105090AA","usgsCitation":"Wynn, Jeff, Orris, G.J., Dunlap, Pamela, Cocker, M.D., and Bliss, J.D., 2016, Geology and undiscovered resource assessment of the potash-bearing Central Asia Salt Basin, Turkmenistan, Uzbekistan, Tajikistan, and Afghanistan: U.S. Geological Survey Scientific Investigations Report SIR 2010–5090–AA, 106 p., and spatial data, https://dx.doi.org/10.3133/sir20105090AA.","productDescription":"Report: xi, 106 p.; GIS Data","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-053583","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":318376,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2010/5090/aa/sir20105090aa.pdf","text":"Report","size":"7.8 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2010-5090-AA report PDF"},{"id":318377,"rank":3,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/sir/2010/5090/aa/sir20105090aa_gis.zip","text":"GIS Data","size":"4.1 MB","linkFileType":{"id":6,"text":"zip"},"description":"SIR 2010-5090-AA GIS Data"},{"id":318375,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2010/5090/aa/coverthb.jpg"}],"country":"Afghanistan, Tajikistan, Turkmenistan, Uzbekistan","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n 62.38037109374999,\n 40.094882122321174\n ],\n [\n 60.3369140625,\n 40.01078714046552\n ],\n [\n 61.14990234374999,\n 36.89719446989036\n ],\n [\n 70.07080078125,\n 35.94243575255426\n ],\n [\n 70.24658203125,\n 37.94419750075404\n ],\n [\n 70.9716796875,\n 38.94232097947902\n ],\n [\n 62.38037109374999,\n 40.094882122321174\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Mineral Resources Program
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http://minerals.usgs.gov/
Since 2012, a multi-agency initiative to restore these native forage species has been under way. Evaluating the restoration success of Cisco Coregonus artedi and Bloater C. hoyi in Lake Ontario waters requires methods to identify stocked fish. However, juvenile Cisco and Bloater are fragile; thus, mass marking techniques that reduce the handling of individual fish are required and have not previously been evaluated. In 2014–2015 we evaluated the usefulness of calcein (SE-MARK) as a marker on bony structures, including the otolith. Juvenile Bloater and Cisco (14, 100, 128 d old) were immersed in a calcein bath at 5,000 mg/L of water for 4 min to apply the chemical marker. Observations of the marking retention were evaluated 8 d following the treatment. All fish immersed in calcein had strong brilliant marks (rating scale 3) on all bony structures including scales, fin rays, jaw bones, and vertebrate. The otolith was the only hard structure that did not show a brilliant marking due to the opaque nature of the structure. Our results suggest that calcein produces a strong discernable mark on hard bony structures of Cisco and Bloater; however, long-term retention needs further study.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/15222055.2016.1143419","usgsCitation":"Chalupnicki, M.A., Mackey, G., Nash, K., Chiavelli, R., Johnson, J.H., Kehler, T., and Ringler, N.H., 2016, Mark retention of calcein in Cisco and Bloater: North American Journal of Aquaculture, v. 78, no. 2, p. 148-153, https://doi.org/10.1080/15222055.2016.1143419.","productDescription":"5 p.","startPage":"148","endPage":"153","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070308","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":325476,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United States","otherGeospatial":"Lake Ontario","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -76.5087890625,\n 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Center","active":true,"usgs":true}],"preferred":true,"id":642948,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Chiavelli, Richard rchiavelli@usgs.gov","contributorId":173000,"corporation":false,"usgs":true,"family":"Chiavelli","given":"Richard","email":"rchiavelli@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":642949,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Johnson, James H. 0000-0002-5619-3871 jhjohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-5619-3871","contributorId":389,"corporation":false,"usgs":true,"family":"Johnson","given":"James","email":"jhjohnson@usgs.gov","middleInitial":"H.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":642950,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Kehler, Thomas","contributorId":168583,"corporation":false,"usgs":false,"family":"Kehler","given":"Thomas","email":"","affiliations":[{"id":5128,"text":"U.S. Fish and Wildlife Service, University of Montana, Missoula, MT 59812","active":true,"usgs":false}],"preferred":false,"id":642951,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ringler, Neil H.","contributorId":28936,"corporation":false,"usgs":true,"family":"Ringler","given":"Neil","email":"","middleInitial":"H.","affiliations":[],"preferred":false,"id":642952,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70169017,"text":"fs20163007 - 2016 - Landscape ecology of the Upper Mississippi River System: Lessons learned, challenges and opportunities","interactions":[],"lastModifiedDate":"2016-06-24T09:07:49","indexId":"fs20163007","displayToPublicDate":"2016-03-22T14:30:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2016-3007","title":"Landscape ecology of the Upper Mississippi River System: Lessons learned, challenges and opportunities","docAbstract":"The Upper Mississippi River System (UMRS) is a mosaic of river channels, backwater lakes, floodplain forests, and emergent marshes. This complex mosaic supports diverse aquatic and terrestrial plant communities, over 150 fish species; 40 freshwater mussel species; 50 amphibian and reptile species; and over 360 bird species, many of which use the UMRS as a critical migratory route. The river and floodplain are also hotspots for biogeochemical activity as the river-floodplain collects and processes nutrients derived from the UMR basin. These features qualify the UMRS as a Ramsar wetland of international significance.
Two centuries of land-use change, including construction for navigation and conversion of large areas to agriculture, has altered the broad-scale structure of the river and changed local environmental conditions in many areas. Such changes have affected rates of nutrient processing and transport, as well as the abundance of various fish, mussel, plant, and bird species. However, the magnitude and spatial scale of these effects are not well quantified, especially in regards to the best methods and locations for restoring various aspects of the river ecosystem.
The U.S. Congress declared the navigable portions of the Upper Mississippi River System (UMRS) a “nationally significant ecosystem and nationally significant commercial navigation system” in the Water Resources Development Act of 1986 (Public Law 99-662) and launched the Upper Mississippi River Restoration (UMRR) Program, the first comprehensive program for ecosystem restoration, monitoring, and research on a large river system. This fact sheet focuses on landscape ecological studies conducted by the U.S. Geological Survey to support decision making by the UMRR with respect to ecosystem restoration.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20163007","collaboration":"A Product of the U.S. Army Corps of Engineers’ Upper Mississippi River Restoration (UMRR) Program","usgsCitation":"De Jager, N., 2016, Landscape Ecology of the Upper Mississippi River System: Lessons learned, challenges and opportunities. U.S. Geological Survey Fact Sheet 2016–3007, 4 p., https://dx.doi.org/10.3133/fs20163007.","productDescription":"4 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-041434","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":318908,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2016/3007/coverthb.jpg"},{"id":318909,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2016/3007/fs20163007.pdf","text":"Report","size":"6.58 MB","description":"FS 2016-3007"}],"country":"United States","otherGeospatial":"Upper Mississippi River System","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -89.62646484375,\n 36.4566360115962\n ],\n [\n -91.47216796875,\n 38.41055825094609\n ],\n [\n -93.93310546875,\n 39.7240885773337\n ],\n [\n -95.44921875,\n 40.48038142908172\n ],\n [\n -96.328125,\n 42.391008609205045\n ],\n [\n -96.50390625,\n 44.26093725039923\n ],\n [\n -96.52587890625,\n 45.19752230305685\n ],\n [\n -95.108642578125,\n 46.21785176740299\n ],\n [\n -94.09790039062499,\n 46.39998810407942\n ],\n [\n -92.735595703125,\n 46.51351558059737\n ],\n [\n -92.17529296875,\n 46.44542749723387\n ],\n [\n -90.3076171875,\n 44.94924926661153\n ],\n [\n -89.197998046875,\n 43.40504748787035\n ],\n [\n -88.22021484375,\n 42.706659563510385\n ],\n [\n -87.791748046875,\n 42.439674178149424\n ],\n [\n -87.60498046875,\n 40.830436877649255\n ],\n [\n -88.187255859375,\n 38.993572058209466\n ],\n [\n -88.53881835937499,\n 37.52715361723378\n ],\n [\n -89.527587890625,\n 36.5184659896759\n ],\n [\n -89.62646484375,\n 36.4566360115962\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Upper Midwest Environmental Sciences Center
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http://www.umesc.usgs.gov/ltrmp.html
Bioremediation strategies, including bioaugmentation with chlorinated ethene-degrading enrichment cultures, have been successfully applied in the cleanup of subsurface environments contaminated with tetrachloroethene (PCE) and/or trichloroethene (TCE). However, these compounds are frequently found in the environment as components of mixtures that may also contain chlorinated ethanes and methanes. Under these conditions, the implementation of bioremediation may be complicated by inhibition effects, particularly when multiple dehalorespirers are present. We investigated the ability of the 1,1,2,2-tetrachloroethane (TeCA)-dechlorinating culture WBC-2 to biotransform TeCA alone, or a mixture of TeCA plus PCE and carbon tetrachloride (CT), in microcosms. The microcosms contained electron donors provided to biostimulate the added culture and sediment collected from a wetland where numerous “hotspots” of contamination with chlorinated solvent mixtures exist. The dominant TeCA biodegradation mechanism mediated by the WBC-2 culture in the microcosms was different in the presence of these wetland sediments than in the sediment-free enrichment culture or in previous WBC-2 bioaugmented microcosms and column tests conducted with wetland sediment collected at nearby sites. The co-contaminants and their daughter products also inhibited TeCA biodegradation by WBC-2. These results highlight the need to conduct biodegradability assays at new sites, particularly when multiple contaminants and dehalorespiring populations are present.
","language":"English","publisher":"Elsevier","doi":"10.1016/j.chemosphere.2015.12.033","collaboration":"U.S. Army, Aberdeen Proving Ground (Maryland)","usgsCitation":"Lorah, M.M., Schiffmacher, E.N., Becker, J.G., and Voytek, M.A., 2016, The effects of co-contaminants and native wetland sediments on the activity and dominant transformation mechanisms of a 1,1,2,2-tetrachloroethane (TeCA)-degrading enrichment culture: Chemosphere, v. 147, p. 239-247, https://doi.org/10.1016/j.chemosphere.2015.12.033.","productDescription":"9 p.","startPage":"239","endPage":"247","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069806","costCenters":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"links":[{"id":488787,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chemosphere.2015.12.033","text":"Publisher Index Page"},{"id":324363,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"147","publishingServiceCenter":{"id":10,"text":"Baltimore PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"576e59b6e4b07657d1a43caf","chorus":{"doi":"10.1016/j.chemosphere.2015.12.033","url":"http://dx.doi.org/10.1016/j.chemosphere.2015.12.033","publisher":"Elsevier BV","authors":"Schiffmacher Emily N., Becker Jennifer G., Lorah Michelle M., Voytek Mary A.","journalName":"Chemosphere","publicationDate":"3/2016","publiclyAccessibleDate":"1/13/2017"},"contributors":{"authors":[{"text":"Lorah, Michelle M. 0000-0002-9236-587X mmlorah@usgs.gov","orcid":"https://orcid.org/0000-0002-9236-587X","contributorId":1437,"corporation":false,"usgs":true,"family":"Lorah","given":"Michelle","email":"mmlorah@usgs.gov","middleInitial":"M.","affiliations":[{"id":374,"text":"Maryland Water Science Center","active":true,"usgs":true}],"preferred":true,"id":640693,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Schiffmacher, Emily N.","contributorId":172429,"corporation":false,"usgs":false,"family":"Schiffmacher","given":"Emily","email":"","middleInitial":"N.","affiliations":[{"id":590,"text":"U.S. Army Corps of Engineers","active":false,"usgs":false}],"preferred":false,"id":640694,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Becker, Jennifer G.","contributorId":172430,"corporation":false,"usgs":false,"family":"Becker","given":"Jennifer","email":"","middleInitial":"G.","affiliations":[{"id":27038,"text":"Michigan Technological University and University of Maryland, College Park","active":true,"usgs":false}],"preferred":false,"id":640696,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Voytek, Mary A.","contributorId":91943,"corporation":false,"usgs":true,"family":"Voytek","given":"Mary","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":640695,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70169142,"text":"ds983 - 2016 - Water temperature profiles for reaches of the Raging River during summer baseflow, King County, western Washington, July 2015","interactions":[],"lastModifiedDate":"2016-03-23T08:58:18","indexId":"ds983","displayToPublicDate":"2016-03-22T12:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":310,"text":"Data Series","code":"DS","onlineIssn":"2327-638X","printIssn":"2327-0271","active":false,"publicationSubtype":{"id":5}},"seriesNumber":"983","title":"Water temperature profiles for reaches of the Raging River during summer baseflow, King County, western Washington, July 2015","docAbstract":"Re-introducing wood into rivers where it was historically removed is one approach to improving habitat conditions in rivers of the Pacific Northwest. The Raging River drainage basin, which flows into the Snoqualmie River at Fall City, western Washington, was largely logged during the 20th century and wood was removed from its channel. To improve habitat conditions for several species of anadromous salmonids that spawn and rear in the Raging River, King County Department of Transportation placed untethered log jams in a 250-meter reach where wood was historically removed. The U.S. Geological Survey measured longitudinal profiles of near-streambed temperature during summer baseflow along 1,026 meters of channel upstream, downstream, and within the area of wood placements. These measurements were part of an effort by King County to monitor the geomorphic and biological responses to these wood placements. Near-streambed temperatures averaged over about 1-meter intervals were measured with a fiber‑optic distributed temperature sensor every 30 minutes for 7 days between July 7 and 13, 2015. Vertical temperature profiles were measured coincident with the longitudinal temperature profile at four locations at 0 centimeters (cm) (at the streambed), and 35 and 70 cm beneath the streambed to document thermal dynamics of the hyporheic zone and surface water in the study reach.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds983","collaboration":"Prepared in cooperation with King County Department of Natural Resource and Parks","usgsCitation":"Gendaszek, A.S., and Opatz, C.C., 2016, Water temperature profiles for reaches of the Raging River during summer baseflow, King County, western Washington, July 2015: U.S. Geological Survey Data Series 983, 8 p.,\nhttps://dx.doi.org/10.3133/ds983.","productDescription":"Report: iii, 8 p.; Tables 1-3","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-070544","costCenters":[{"id":622,"text":"Washington Water Science Center","active":true,"usgs":true}],"links":[{"id":319142,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0983/coverthb.jpg"},{"id":319143,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0983/ds983.pdf","text":"Report","size":"4.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 983"},{"id":319144,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0983/ds983_table01.xlsx","text":"Table 1","size":"1.2 MB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 983 Table 1"},{"id":319145,"rank":4,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0983/ds983_table02.xlsx","text":"Table 2","size":"56 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 983 Table 2"},{"id":319146,"rank":5,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0983/ds983_table03.xlsx","text":"Table 3","size":"70 KB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 983 Table 3"}],"country":"United States","state":"Washington","county":"King County","otherGeospatial":"Raging River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.8639,\n 47.45\n ],\n [\n -121.8639,\n 47.4569\n ],\n [\n -121.8583,\n 47.4569\n ],\n [\n -121.8583,\n 47.45\n ],\n [\n -121.8639,\n 47.45\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Washington Water Science Center
U.S. Geological Survey
934 Broadway, Suite 300
Tacoma, Washington 98402
http://wa.water.usgs.gov
Seepage investigations have been conducted annually by the U.S. Geological Survey from 1988 to 1998 and from 2004 to the present (2014) along a 64-mile reach of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, as part of the Mesilla Basin monitoring program. Results of the investigation conducted in 2014 are presented in this report. The 2014 seepage investigation was conducted on February 11, 2014, during the low-flow conditions of the non-irrigation season. During the 2014 investigation, discharge was measured at 23 sites along the main-stem Rio Grande and 19 inflow sites within the study reach. Because of extended drought conditions affecting the basin, many sites along the Rio Grande (17 main-stem and 9 inflow) were observed to be dry in February 2014. Water-quality samples were collected during the seepage investigation at sites with flowing water as part of a long-term monitoring effort in the region.
Net seepage gain or loss was computed for each subreach (the interval between two adjacent measurement locations along the river) by subtracting the discharge measured at the upstream location from the discharge measured at the closest downstream location along the river and then subtracting any inflow to the river within the subreach. An estimated gain or loss was determined to be meaningful when it exceeded the cumulative measurement uncertainty associated with the net seepage computation. The cumulative seepage loss in the 64-mile study reach in 2014 was 16.0 plus or minus 2.9 cubic feet per second.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165010","usgsCitation":"Briody, A.C., Robertson, A.J., and Thomas, Nicole, 2016, Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, 2014: U.S. Geological Survey Scientific Investigations Report 2016–5010, 15 p., https://dx.doi.org/10.3133/sir20165010.","productDescription":"Report: vi, 12 p., Appendix: 3 p.","numberOfPages":"15","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-068494","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":319116,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5010/coverthb.jpg"},{"id":319117,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5010/sir20165010.pdf","text":"Report","size":"3.15 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5010"}],"country":"United States","state":"New Mexico, Texas","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.9,\n 32.5\n ],\n [\n -106.9,\n 31.75\n ],\n [\n -106.5,\n 31.75\n ],\n [\n -106.5,\n 32.5\n ],\n [\n -106.9,\n 32.5\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montogmery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
This report, prepared by the U.S. Geological Survey in cooperation with the Kansas Department of Agriculture, Division of Water Resources, presents derivative statistics of 2013 irrigation water use in Kansas. The published regional and county-level statistics from the previous 4 years (2009–12) are shown with the 2013 statistics and are used to calculate a 5-year average. An overall Kansas average and regional averages also are calculated and presented. Total reported irrigation water use in 2013 was 3.3 million acre-feet of water applied to 3.0 million irrigated acres.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ds981","collaboration":"Prepared in cooperation with the Kansas Department of Agriculture, Division of Water Resources","usgsCitation":"Lanning-Rush, J.L., 2016, Irrigation water use in Kansas, 2013: U.S. Geological Survey Data Series 981, 12 p., https://dx.doi.org/10.3133/ds981.","productDescription":"Report: iv, 12 p.; Tables 6-12; Appendix: 2 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-070156","costCenters":[{"id":353,"text":"Kansas Water Science Center","active":false,"usgs":true}],"links":[{"id":318889,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/ds/0981/ds981.pdf","text":"Report","size":"617 kB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 981"},{"id":318890,"rank":3,"type":{"id":27,"text":"Table"},"url":"https://pubs.usgs.gov/ds/0981/downloads/ds981_tables6to12.xlsx","text":"Tables 6–12","size":"80 kB","linkFileType":{"id":3,"text":"xlsx"},"description":"DS 981 Tables "},{"id":318888,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/ds/0981/coverthb_new.jpg"},{"id":318893,"rank":4,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/ds/0981/downloads/ds981_appendix.pdf","text":"Water-Use Report","size":"1.34 MB","linkFileType":{"id":1,"text":"pdf"},"description":"DS 981 Appendix"}],"country":"United States","state":"Kansas","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -95.29541015625,\n 39.99395569397331\n ],\n [\n -102.06298828125,\n 40.01078714046552\n ],\n [\n -102.052001953125,\n 36.98500309285596\n ],\n [\n -94.603271484375,\n 36.99377838872517\n ],\n [\n -94.6142578125,\n 39.13006024213511\n ],\n [\n -94.76806640624999,\n 39.172658670429946\n ],\n [\n -94.82299804687499,\n 39.2407625100131\n ],\n [\n -94.910888671875,\n 39.29179704377487\n ],\n [\n -94.8779296875,\n 39.38526381099777\n ],\n [\n -94.976806640625,\n 39.436192999314095\n ],\n [\n -95.086669921875,\n 39.53793974517628\n ],\n [\n -95.042724609375,\n 39.57182223734374\n ],\n [\n -95.042724609375,\n 39.63953756436671\n ],\n [\n -94.9658203125,\n 39.73253798438173\n ],\n [\n -94.910888671875,\n 39.73253798438173\n ],\n [\n -94.888916015625,\n 39.78321267821705\n ],\n [\n -94.910888671875,\n 39.842286020743394\n ],\n [\n -94.95483398437499,\n 39.8928799002948\n ],\n [\n -95.03173828125,\n 39.90973623453719\n ],\n [\n -95.06469726562499,\n 39.87601941962116\n ],\n [\n -95.174560546875,\n 39.926588421909436\n ],\n [\n -95.29541015625,\n 39.99395569397331\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Kansas Water Science Center
U.S. Geological Survey
4821 Quail Crest Place
Lawrence, KS 66049
Digital flood-inundation maps for a 12.5-mile reach of the Big Papillion Creek from 0.6 mile upstream from the State Street Bridge to the 72nd Street Bridge in Omaha, Nebraska, were created by the U.S. Geological Survey (USGS) in cooperation with the Papio-Missouri River Natural Resources District. The flood-inundation maps, which can be accessed through the USGS Flood Inundation Mapping Science Web site at http://water.usgs.gov/osw/flood_inundation/, depict estimates of the areal extent and depth of flooding corresponding to selected water levels (stages) at the USGS streamgage on the Big Papillion Creek at Fort Street at Omaha, Nebraska (station 06610732). Near-real-time stages at this streamgage may be obtained on the Internet from the USGS National Water Information System at http://waterdata.usgs.gov/ or the National Weather Service Advanced Hydrologic Prediction Service at http:/water.weather.gov/ahps/, which also forecasts flood hydrographs at this site.
\nFlood profiles were computed for the 12.5-mile reach by means of a one-dimensional step-backwater model. The model was calibrated by using the current (2015) stage-discharge relation at streamgages for the Big Papillion Creek at Fort Street at Omaha, Nebraska, and the Big Papillion Creek at Q Street at Omaha, Nebraska. The hydraulic model was then used to compute 15 water-surface profiles for flood stages at 1-foot (ft) intervals referenced to the streamgage datum for the Big Papillion Creek at Fort Street and ranging from 18 ft (or near bankfull) to 32 ft, which exceeds the “major flood stage” as defined by the National Weather Service. The simulated water-surface profiles were then combined with a Geographic Information System digital elevation model (derived from light detection and ranging data having a 1.18-ft vertical accuracy and 3.28-ft horizontal resolution) to delineate the area flooded at each flood stage (water level).
\nThe availability of these flood-inundation maps, along with Internet information regarding current stage from the USGS streamgage and forecasted high-flow stages from the National Weather Service, will provide emergency management personnel and residents with information that is critical for flood response activities such as evacuations and road closures, as well as for postflood recovery efforts.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155152","collaboration":"Prepared in cooperation with the Papio-Missouri River Natural Resources District","usgsCitation":"Strauch, K.R., Dietsch, B.J., and Anderson, K.J., 2016, Flood-inundation maps for a 12.5-mile reach of Big Papillion Creek at Omaha, Nebraska: U.S. Geological Survey Scientific Investigations Report 2015–5152, 11 p., https://dx.doi.org/10.3133/sir20155152.","productDescription":"Report: v, 11 p.; Datasets; Metadata","numberOfPages":"11","onlineOnly":"Y","additionalOnlineFiles":"Y","ipdsId":"IP-066029","costCenters":[{"id":464,"text":"Nebraska Water Science Center","active":true,"usgs":true}],"links":[{"id":314625,"rank":5,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_river_areas_GRIDS.zip","text":"River area GRIDS","size":"52.9 MB","description":"SIR 2015–5152 River area GRIDS"},{"id":314626,"rank":6,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_river_areas_shapefiles.zip","text":"River area shapefiles","size":"2.2 MB","description":"SIR 2015–5152 River area shapefiles"},{"id":314628,"rank":7,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_metadata_BigPapio_at_Fort_FIM_GRID.txt","text":"GRID metadata","size":"20.0 kb","description":"SIR 2015–5152 GRID metadata"},{"id":314629,"rank":8,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_metadata_BigPapio_at_Fort_FIM_shapefile.txt","text":"Shapefile metadata","size":"20.0 kb","description":"SIR 2015–5152 Shapefile metadata"},{"id":314466,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152.pdf","text":"Report","size":"2.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5152"},{"id":314622,"rank":3,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_levee_areas_GRIDS.zip","text":"Levee area GRIDS","size":"1.6 MB","description":"SIR 2015–5152 Levee area GRIDS"},{"id":314623,"rank":4,"type":{"id":28,"text":"Dataset"},"url":"https://pubs.usgs.gov/sir/2015/5152/sir20155152_dataset_levee_areas_shapefiles.zip","text":"Levee area shapefiles","size":"144 kb","description":"SIR 2015–5152 Levee area shapefiles"},{"id":314465,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5152/coverthb.jpg"}],"country":"United States","state":"Nebraska","city":"Omaha","otherGeospatial":"Big Papillion Creek","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -96.16676330566406,\n 41.23702755320388\n ],\n [\n -96.16676330566406,\n 41.35052580597025\n ],\n [\n -96.01020812988281,\n 41.35052580597025\n ],\n [\n -96.01020812988281,\n 41.23702755320388\n ],\n [\n -96.16676330566406,\n 41.23702755320388\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Nebraska Water Science Center
U.S. Geological Survey
5231 South 19th Street
Lincoln, NE 68512
Seepage investigations have been conducted annually by the U.S. Geological Survey from 1988 to 1998 and from 2004 to the present (2015) along a 64-mile reach of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, as part of the Mesilla Basin monitoring program. Results of the investigation conducted in 2015 are presented in this report. The 2015 seepage investigation was conducted on February 10, 2015, during the low-flow conditions of the non-irrigation season. During the 2015 investigation, discharge was measured at 23 sites along the main-stem Rio Grande and 19 inflow sites within the study reach. Because of extended drought conditions affecting the basin, many sites along the Rio Grande (17 main-stem and 10 inflow) were observed to be dry in February 2015.
\nNet seepage gain or loss was computed for each subreach (the interval between two adjacent measurement locations along the river) by subtracting the discharge measured at the upstream location from the discharge measured at the closest downstream location along the river and then subtracting any inflow to the river within the subreach. An estimated gain or loss was determined to be meaningful when it exceeded the cumulative measurement uncertainty associated with the net seepage computation. The cumulative seepage loss in the 64-mile study reach in 2015 was 17.3 plus or minus 2.6 cubic feet per second. Gaining and losing reaches identified in this investigation generally correspond to seepage patterns observed in previous investigations conducted during dry years, with the gaining reaches occurring primarily at the southern (downstream) end of the basin.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20165011","usgsCitation":"Briody, A.C., Robertson, A.J., and Thomas, Nicole, 2016, Seepage investigation of the Rio Grande from below Leasburg Dam, Leasburg, New Mexico, to above American Dam, El Paso, Texas, 2015: U.S. Geological Survey Scientific Investigations Report 2016–5011, 15 p., https://dx.doi.org/10.3133/sir20165011.","productDescription":"vi., 15 p.","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069688","costCenters":[{"id":472,"text":"New Mexico Water Science Center","active":true,"usgs":true}],"links":[{"id":319125,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2016/5011/sir20165011.pdf","text":"Report","size":"3.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2016–5011"},{"id":319124,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2016/5011/coverthb.jpg"}],"country":"United States","otherGeospatial":"Rio Grande","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -106.85302734374999,\n 31.728167146023935\n ],\n [\n -106.85302734374999,\n 32.41706632846282\n ],\n [\n -106.3970947265625,\n 32.41706632846282\n ],\n [\n -106.3970947265625,\n 31.728167146023935\n ],\n [\n -106.85302734374999,\n 31.728167146023935\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, New Mexico Water Science Center
U.S. Geological Survey
5338 Montogmery Blvd., NE Suite 400
Albuquerque, NM 87109–1311
The U.S. Geological Survey (USGS), in cooperation with the City of Houston, began a study in 2007 to determine concentrations, spatial extent, and associated geochemical conditions that might be conducive for mobility and transport of selected naturally occurring trace elements and radionuclides in the Gulf Coast aquifer system in Houston, Texas. Water samples were collected from 91 municipal supply wells completed in the Evangeline and Chicot aquifers of the Gulf Coast aquifer system in northeastern, northwestern, and southwestern Houston; hereinafter referred to as northeast, northwest and southwest Houston areas. Wells were sampled in three phases: (1) 28 municipal supply wells were sampled during 2007–8, (2) 60 municipal supply wells during 2010, and (3) 3 municipal supply wells during December 2011. During each phase of sampling, samples were analyzed for major ions, selected trace elements, and radionuclides. At a subset of wells, concentrations of arsenic species and other radionuclides (carbon-14, radium-226, radium-228, radon-222, and tritium) also were analyzed. Selected physicochemical properties were measured in the field at the time each sample was collected, and oxidation-reduction potential and unfiltered sulfides also were measured at selected wells. The source-water (the raw, ambient water withdrawn from municipal supply wells prior to water treatment) samples were collected for assessment of aquifer conditions in order to provide community water-system operators information that could be important when they make decisions about which treatment processes to apply before distributing finished drinking water.
\nGeochemical conditions of groundwater of the Gulf Coast aquifer system are suitable in some instances for release of arsenic and radionuclides from aquifer materials. Recent changes to the U.S. Environmental Protection Agency (EPA) primary drinking-water regulations for arsenic and a selected number of natural radionuclides have highlighted the necessity for municipal supply system managers to be aware of the occurrence and distribution of these constituents in their source water. Concentrations of arsenic ranged from 0.58 to 23.5 micrograms per liter (μg/L), with relatively low median and 75th percentile concentrations (2.7 and 3.6 μg/L, respectively). The gross alpha-particle activity completed within 72 hours after sample collection ranged from R-1.1 (nondetect where the result was below the sample specific critical level) to 39.7 picocuries per liter (pCi/L), with a median of 10.3 pCi/L. After 30 days, the gross alpha-particle activities in the 91 samples ranged from R-0.94 to 25.5 pCi/L, with a median of 5.60 pCi/L. Concentrations of uranium ranged from less than 0.02 to 42.7 μg/L, with a median value of 1.69 μg/L and a 75th-percentile value of 6.48 μg/L. The maximum concentrations of radium-226 and combined radium (sum of radium-226 plus radium-228) were 4.34 pCi/L and 3.23 pCi/L, respectively.
\nAquifer major-ion geochemistry was characterized and shown to contain three chemical types of water as grouped by a simplified predominant cation and anion classification system: (1) calcium- bicarbonate type, (2) sodium-bicarbonate type, and (3) sodium-chloride type. Aquifer geochemistry also was characterized into four reduction-oxidation (redox) categories: (1) oxic, (2) suboxic, (3) mixed, and (4) anoxic. Within the anoxic category, groundwater was further characterized into four presumed predominant reduction processes: (1) iron or sulfate or both [Fe(III)/SO4] reducing, (2) iron [Fe(III)] reducing, (3) iron and sulfate [Fe(III)-SO4] reducing, or (4) methanogenic, as defined by composition of redox species. The oxic category was associated with calcium-bicarbonate-type water, and the methanogenic-anoxic process was associated exclusively with the sodium-bicarbonate-type water. The species of arsenic and the dominant radionuclide present were associated with specific redox categories. Arsenate was associated primarily with oxic water and did not exceed 3.5 µg/L, whereas arsenite was associated with iron-reducing, anoxic water samples and, at the highest concentrations, occurred in sulfate-reducing, anoxic; methanogenic-anoxic; or both water samples. Uranium was associated exclusively with the oxic water, whereas the highest concentrations of combined radium were associated with the iron-reducing, anoxic water. The gross alpha-particle activity was greatest in the oxic waters where the source of the radioactivity was the uranium.
\nAssociated geochemical conditions conducive for mobility of arsenic and radionuclides and their spatial and vertical extent in the Gulf Coast aquifer system in Houston are important aspects to the areal management of the municipal groundwater supplies in Houston. Ongoing research is seeking to define chemical or geological factors that are the optimal indicators for elevated concentrations of these naturally occurring constituents.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20155071","collaboration":"Prepared in cooperation with the City of Houston","usgsCitation":"Oden, J.H., and Szabo, Zoltan, 2015, Arsenic and radionuclide occurrence and relation to geochemistry in groundwater of the Gulf Coast Aquifer System in Houston, Texas, 2007–11: U.S. Geological Scientific Investigations Report 2015–5071, 105 p., 4 apps., https://dx.doi.org/10.3133/sir20155071.","productDescription":"Report: xi, 105 p.; Appendixes: 29 p. ","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-055471","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":318941,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2015/5071/coverthb.jpg"},{"id":318942,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2015/5071/sir20155071.pdf","text":"Report","size":"3.38 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5071"},{"id":318943,"rank":3,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2015/5071/sir20155071_appendix1to4.pdf","text":"Appendixes 1–4","size":"428 kB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2015–5071 Appendixes 1–4"}],"country":"United States","state":"Texas","city":"Houston","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -94.35333251953125,\n 29.5232805008286\n ],\n [\n -94.515380859375,\n 29.441989466225706\n ],\n [\n -94.64996337890625,\n 29.351057685705033\n ],\n [\n -94.84222412109375,\n 29.216904948184734\n ],\n [\n -95.05645751953124,\n 29.048966726566885\n ],\n [\n -95.3118896484375,\n 28.86632376895912\n ],\n [\n -95.53436279296875,\n 28.878349647602047\n ],\n [\n -95.75958251953125,\n 29.07297469064491\n ],\n [\n -95.877685546875,\n 29.27202470909843\n ],\n [\n -95.92987060546874,\n 29.34148119149953\n ],\n [\n -95.98480224609374,\n 29.420460341013133\n ],\n [\n -96.03973388671875,\n 29.44916482692468\n ],\n [\n -96.06170654296875,\n 29.49698759653577\n ],\n [\n -96.02325439453124,\n 29.508939763268394\n ],\n [\n -96.0589599609375,\n 29.554345125748267\n ],\n [\n -96.08367919921875,\n 29.587788659909958\n ],\n [\n -96.0205078125,\n 29.633158589140564\n ],\n [\n -96.05072021484375,\n 29.680894340704334\n ],\n [\n -96.0040283203125,\n 29.702368038541767\n ],\n [\n -96.01776123046875,\n 29.716681287231072\n ],\n [\n -96.04522705078125,\n 29.728607435707517\n ],\n [\n -96.05072021484375,\n 29.790600550959457\n ],\n [\n -96.1029052734375,\n 29.81205076752506\n ],\n [\n -96.119384765625,\n 29.87637380707133\n ],\n [\n -96.12487792968749,\n 29.938275329718987\n ],\n [\n -96.10015869140625,\n 29.99775972557893\n ],\n [\n -96.12487792968749,\n 30.035811042667792\n ],\n [\n -96.1578369140625,\n 30.083354648756153\n ],\n [\n -96.17980957031249,\n 30.128499916692782\n ],\n [\n -96.1688232421875,\n 30.171250084367482\n ],\n [\n -96.119384765625,\n 30.225848323247707\n ],\n [\n -96.09466552734375,\n 30.28041626667403\n ],\n [\n -96.14410400390625,\n 30.334953881988564\n ],\n [\n -96.16333007812499,\n 30.37761431777479\n ],\n [\n -96.185302734375,\n 30.4060442699695\n ],\n [\n -96.2347412109375,\n 30.441570071519443\n ],\n [\n -95.7623291015625,\n 30.68988785772121\n ],\n [\n -95.30914306640625,\n 30.904581367044212\n ],\n [\n -95.240478515625,\n 30.871582821957446\n ],\n [\n -95.22125244140625,\n 30.831497881307943\n ],\n [\n -95.16357421875,\n 30.7937555812177\n ],\n [\n -95.13885498046875,\n 30.741835717889792\n ],\n [\n -95.108642578125,\n 30.69697330439986\n ],\n [\n -95.00976562499999,\n 30.652090026760014\n ],\n [\n -95.00976562499999,\n 30.62373195163005\n ],\n [\n -95.0372314453125,\n 30.58354378627138\n ],\n [\n -94.976806640625,\n 30.576450026618076\n ],\n [\n -94.9273681640625,\n 30.56462594065098\n ],\n [\n -94.85321044921875,\n 30.545704405480997\n ],\n [\n -94.866943359375,\n 30.517315187761888\n ],\n [\n -94.83673095703125,\n 30.479449996609706\n ],\n [\n -94.8834228515625,\n 30.462879341709886\n ],\n [\n -94.8394775390625,\n 30.439202087235607\n ],\n [\n -94.7955322265625,\n 30.38472258144958\n ],\n [\n -94.7735595703125,\n 30.344435586368462\n ],\n [\n -94.78729248046875,\n 30.299389313522617\n ],\n [\n -94.61151123046875,\n 30.097613277217132\n ],\n [\n -94.52636718749999,\n 29.971590978566113\n ],\n [\n -94.44122314453124,\n 29.816816857649936\n ],\n [\n -94.37805175781249,\n 29.676121784724305\n ],\n [\n -94.35333251953125,\n 29.5232805008286\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Director, Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754–4501
Cold-water corals, similar to tropical corals, contain diverse and complex microbial assemblages. These bacteria provide essential biological functions within coral holobionts, facilitating increased nutrient utilization and production of antimicrobial compounds. To date, few cold-water octocoral species have been analyzed to explore the diversity and abundance of their microbial associates. For this study, 23 samples of the family Anthothelidae were collected from Norfolk (n = 12) and Baltimore Canyons (n = 11) from the western Atlantic in August 2012 and May 2013. Genetic testing found that these samples comprised two Anthothela species (Anthothela grandiflora and Anthothela sp.) and Alcyonium grandiflorum. DNA was extracted and sequenced with primers targeting the V4-V5 variable region of the 16S rRNA gene using 454 pyrosequencing with GS FLX Titanium chemistry. Results demonstrated that the coral host was the primary driver of bacterial community composition. Al. grandiflorum, dominated by Alteromonadales and Pirellulales had much higher species richness, and a distinct bacterial community compared to Anthothela samples. Anthothela species (A. grandiflora and Anthothela sp.) had very similar bacterial communities, dominated by Oceanospirillales and Spirochaetes. Additional analysis of core-conserved bacteria at 90% sample coverage revealed genus level conservation across Anthothela samples. This core included unclassified Oceanospirillales, Kiloniellales, Campylobacterales, and genus Spirochaeta. Members of this core were previously recognized for their functional capabilities in nitrogen cycling and suggest the possibility of a nearly complete nitrogen cycle within Anthothela species. Overall, many of the bacterial associates identified in this study have the potential to contribute to the acquisition and cycling of nutrients within the coral holobiont.
","language":"English","publisher":"Frontiers in Microbiology","doi":"10.3389/fmicb.2016.00458","usgsCitation":"Lawler, S.N., Kellogg, C.A., France, S.C., Clostio, R.W., Brooke, S.D., and Ross, S., 2016, Coral-associated bacterial diversity is conserved across two deep-sea Anthothela species: Frontiers in Microbiology, v. 7, art458: 18 p., https://doi.org/10.3389/fmicb.2016.00458.","productDescription":"art458: 18 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-070380","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":471135,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3389/fmicb.2016.00458","text":"Publisher Index Page"},{"id":319379,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Norfolk Canyon; Baltimore Canyon","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.124755859375,\n 37.60552821745789\n ],\n [\n -74.1357421875,\n 37.322120359451766\n ],\n [\n -73.729248046875,\n 37.31338308990806\n ],\n [\n -73.7567138671875,\n 37.64468458716586\n ],\n [\n -74.124755859375,\n 37.60552821745789\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -73.7841796875,\n 38.55246141354153\n ],\n [\n -73.8720703125,\n 38.33303882235456\n ],\n [\n -73.54248046875,\n 38.302869955150044\n ],\n [\n -73.4326171875,\n 38.50519140240354\n ],\n [\n -73.7841796875,\n 38.55246141354153\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"7","publishingServiceCenter":{"id":8,"text":"Raleigh PSC"},"noUsgsAuthors":false,"publicationDate":"2016-04-05","publicationStatus":"PW","scienceBaseUri":"56f50fb6e4b0f59b85e1ead5","contributors":{"authors":[{"text":"Lawler, Stephanie N.","contributorId":149424,"corporation":false,"usgs":false,"family":"Lawler","given":"Stephanie","email":"","middleInitial":"N.","affiliations":[{"id":17733,"text":"University of South Florida, St. Petersburg, FL","active":true,"usgs":false}],"preferred":false,"id":623799,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kellogg, Christina A. 0000-0002-6492-9455 ckellogg@usgs.gov","orcid":"https://orcid.org/0000-0002-6492-9455","contributorId":391,"corporation":false,"usgs":true,"family":"Kellogg","given":"Christina","email":"ckellogg@usgs.gov","middleInitial":"A.","affiliations":[{"id":506,"text":"Office of the AD Ecosystems","active":true,"usgs":true},{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":623800,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"France, Scott C","contributorId":167845,"corporation":false,"usgs":false,"family":"France","given":"Scott","email":"","middleInitial":"C","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":623801,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Clostio, Rachel W","contributorId":167846,"corporation":false,"usgs":false,"family":"Clostio","given":"Rachel","email":"","middleInitial":"W","affiliations":[{"id":7155,"text":"University of Louisiana at Lafayette","active":true,"usgs":false}],"preferred":false,"id":623802,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Brooke, Sandra D.","contributorId":167844,"corporation":false,"usgs":false,"family":"Brooke","given":"Sandra","email":"","middleInitial":"D.","affiliations":[{"id":24836,"text":"Coastal and Marine Laboratory, Florida State University","active":true,"usgs":false}],"preferred":false,"id":623803,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ross, Steve W.","contributorId":41134,"corporation":false,"usgs":false,"family":"Ross","given":"Steve W.","affiliations":[{"id":32398,"text":"University of North Carolina Wilmington","active":true,"usgs":false}],"preferred":false,"id":623804,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70170076,"text":"70170076 - 2016 - Identifying the origin of waterbird carcasses in Lake Michigan using a neural network source tracking model","interactions":[],"lastModifiedDate":"2016-12-16T11:32:48","indexId":"70170076","displayToPublicDate":"2016-03-19T13:45:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2330,"text":"Journal of Great Lakes Research","active":true,"publicationSubtype":{"id":10}},"title":"Identifying the origin of waterbird carcasses in Lake Michigan using a neural network source tracking model","docAbstract":"Avian botulism type E is responsible for extensive waterbird mortality on the Great Lakes, yet the actual site of toxin exposure remains unclear. Beached carcasses are often used to describe the spatial aspects of botulism mortality outbreaks, but lack specificity of offshore toxin source locations. We detail methodology for developing a neural network model used for predicting waterbird carcass motions in response to wind, wave, and current forcing, in lieu of a complex analytical relationship. This empirically trained model uses current velocity, wind velocity, significant wave height, and wave peak period in Lake Michigan simulated by the Great Lakes Coastal Forecasting System. A detailed procedure is further developed to use the model for back-tracing waterbird carcasses found on beaches in various parts of Lake Michigan, which was validated using drift data for radiomarked common loon (Gavia immer) carcasses deployed at a variety of locations in northern Lake Michigan during September and October of 2013. The back-tracing model was further used on 22 non-radiomarked common loon carcasses found along the shoreline of northern Lake Michigan in October and November of 2012. The model-estimated origins of those cases pointed to some common source locations offshore that coincide with concentrations of common loons observed during aerial surveys. The neural network source tracking model provides a promising approach for identifying locations of botulinum neurotoxin type E intoxication and, in turn, contributes to developing an understanding of the dynamics of toxin production and possible trophic transfer pathways.
","language":"English","publisher":"International Association for Great Lakes Research","doi":"10.1016/j.jglr.2016.02.014","usgsCitation":"Kenow, K.P., Ge, Z., Fara, L.J., Houdek, S.C., and Lubinski, B.R., 2016, Identifying the origin of waterbird carcasses in Lake Michigan using a neural network source tracking model: Journal of Great Lakes Research, v. 42, no. 3, p. 637-648, https://doi.org/10.1016/j.jglr.2016.02.014.","productDescription":"12 p.","startPage":"637","endPage":"648","numberOfPages":"12","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-067361","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":471136,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.jglr.2016.02.014","text":"Publisher Index Page"},{"id":319840,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Canada, United 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Diseases","active":true,"publicationSubtype":{"id":10}},"title":"Survey for West Nile virus antibodies in wild ducks, 2004-06, USA","docAbstract":"Detection of West Nile virus (WNV) in ducks has been reported in North America in isolated cases of mortality in wild waterbirds and following outbreaks in farmed ducks. Although the virus has been noted as an apparent incidental finding in several species of ducks, little is known about the prevalence of exposure or the outcome of infection with WNV in wild ducks in North America. From 2004–06, we collected sera from 1,406 wild-caught American Wigeon (Anas americana), Mallard (Anas platyrhynchos), and Northern Pintail (Anas acuta) ducks at national wildlife refuges (NWRs) in North Dakota and Wood Ducks (Aix sponsa) at NWRs in South Carolina and Tennessee. We measured the prevalence of previous exposure to WNV in these ducks by measuring WNV antibodies and evaluated variation in exposure among species, age, and year. Additionally, we evaluated the performance of a commercial antibody to wild bird immunoglobulin in duck species that varied in their phylogenetic relatedness to the bird species the antibody was directed against. As determined by a screening immunoassay and a confirmatory plaque reduction neutralization assay, the prevalence of WNV antibody was 10%. In light of experimental studies that show ducks to be relatively resistant to mortality caused by WNV, the antibody prevalence we detected suggests that wild ducks may be less-frequently exposed to WNV than expected for birds inhabiting wetlands where they may acquire infection from mosquitoes.
","language":"English","publisher":"Wildlife Disease Association","publisherLocation":"Lawrence, KS","doi":"10.7589/2015-06-137","usgsCitation":"Hofmeister, E.K., Jankowski, M.D., Goldberg, D.R., and Franson, J., 2016, Survey for West Nile virus antibodies in wild ducks, 2004-06, USA: Journal of Wildlife Diseases, v. 52, no. 2, 10 p., https://doi.org/10.7589/2015-06-137.","productDescription":"10 p.","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-069694","costCenters":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"links":[{"id":318954,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"North Dakota, South Carolina, Tennessee","otherGeospatial":"J. Clark Salyer National Wildlife Refuge, Santee National Wildlife Refuge, Savannah National Wildlife Refuge, Tennessee National Wildlife Refuge","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.26235,\n 33.33145\n ],\n [\n -80.26235,\n 33.33135\n ],\n [\n -80.26225,\n 33.33135\n ],\n [\n -80.26225,\n 33.33145\n ],\n [\n -80.26235,\n 33.33145\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -81.06195,\n 32.11255\n ],\n [\n -81.06195,\n 32.11245\n ],\n [\n -81.06185,\n 32.11245\n ],\n [\n -81.06185,\n 32.11255\n ],\n [\n -81.06195,\n 32.11255\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -87.58115,\n 35.57095\n ],\n [\n -87.58115,\n 35.57085\n ],\n [\n -87.58105,\n 35.57085\n ],\n [\n -87.58105,\n 35.57095\n ],\n [\n -87.58115,\n 35.57095\n ]\n ]\n ]\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -100.31315,\n 48.32215\n ],\n [\n -100.31315,\n 48.32205\n ],\n [\n -100.31305,\n 48.32205\n ],\n [\n -100.31305,\n 48.32215\n ],\n [\n -100.31315,\n 48.32215\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"52","issue":"2","publishingServiceCenter":{"id":6,"text":"Columbus PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"56ed18a1e4b0f59b85da9eb1","contributors":{"authors":[{"text":"Hofmeister, Erik K. 0000-0002-6360-3912 ehofmeister@usgs.gov","orcid":"https://orcid.org/0000-0002-6360-3912","contributorId":3230,"corporation":false,"usgs":true,"family":"Hofmeister","given":"Erik","email":"ehofmeister@usgs.gov","middleInitial":"K.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":true,"id":578735,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Jankowski, Mark","contributorId":149535,"corporation":false,"usgs":false,"family":"Jankowski","given":"Mark","affiliations":[{"id":17765,"text":"Present address: Minnesota Pollution Control Agency, 520 Lafayette Road N., St. Paul, MN 55155","active":true,"usgs":false}],"preferred":false,"id":578736,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Goldberg, Diana R. 0000-0001-8540-8512 dgoldberg@usgs.gov","orcid":"https://orcid.org/0000-0001-8540-8512","contributorId":5739,"corporation":false,"usgs":true,"family":"Goldberg","given":"Diana","email":"dgoldberg@usgs.gov","middleInitial":"R.","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":578737,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Franson, J. Christian jfranson@usgs.gov","contributorId":149318,"corporation":false,"usgs":true,"family":"Franson","given":"J. Christian","email":"jfranson@usgs.gov","affiliations":[{"id":456,"text":"National Wildlife Health Center","active":true,"usgs":true}],"preferred":false,"id":578738,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70184175,"text":"70184175 - 2016 - Determination of polydimethylsiloxane–water partition coefficients for ten 1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene-related compounds and twelve polychlorinated biphenyls using gas chromatography/mass spectrometry","interactions":[],"lastModifiedDate":"2017-03-01T14:22:27","indexId":"70184175","displayToPublicDate":"2016-03-18T00:00:00","publicationYear":"2016","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2214,"text":"Journal of Chromatography A","active":true,"publicationSubtype":{"id":10}},"title":"Determination of polydimethylsiloxane–water partition coefficients for ten 1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene-related compounds and twelve polychlorinated biphenyls using gas chromatography/mass spectrometry","docAbstract":"Polymer-water partition coefficients (Kpw) of ten DDT-related compounds were determined in pure water at 25 °C using commercial polydimethylsiloxane-coated optical fiber. Analyte concentrations were measured by thermal desorption-gas chromatography/full scan mass spectrometry (TD–GC/MSFS; fibers) and liquid injection-gas chromatography/selected ion monitoring mass spectrometry (LI–GC/MSSIM; water). Equilibrium was approached from two directions (fiber uptake and depletion) as a means of assessing data concordance. Measured compound-specific log Kpw values ranged from 4.8 to 6.1 with an average difference in log Kpw between the two approaches of 0.05 log units (∼12% of Kpw). Comparison of the experimentally-determined log Kpw values with previously published data confirmed the consistency of the results and the reliability of the method. A second experiment was conducted with the same ten DDT-related compounds and twelve selected PCB (polychlorinated biphenyl) congeners under conditions characteristic of a coastal marine field site (viz., seawater, 11 °C) that is currently under investigation for DDT and PCB contamination. Equilibration at lower temperature and higher ionic strength resulted in an increase in log Kpw for the DDT-related compounds of 0.28–0.49 log units (61–101% of Kpw), depending on the analyte. The increase in Kpw would have the effect of reducing by approximately half the calculated freely dissolved pore-water concentrations (Cfree). This demonstrates the importance of determining partition coefficients under conditions as they exist in the field.","language":"English","publisher":"Elsevier","doi":"10.1016/j.chroma.2016.02.038","usgsCitation":"Eganhouse, R., 2016, Determination of polydimethylsiloxane–water partition coefficients for ten 1-chloro-4-[2,2,2-trichloro-1-(4-chlorophenyl)ethyl]benzene-related compounds and twelve polychlorinated biphenyls using gas chromatography/mass spectrometry: Journal of Chromatography A, v. 1438, p. 226-235, https://doi.org/10.1016/j.chroma.2016.02.038.","productDescription":"10 p.","startPage":"226","endPage":"235","ipdsId":"IP-072715","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":471138,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.chroma.2016.02.038","text":"Publisher Index Page"},{"id":336774,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"},{"id":336715,"type":{"id":15,"text":"Index Page"},"url":"https://www.sciencedirect.com/science/article/pii/S0021967316301376"}],"volume":"1438","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"58b7eba8e4b01ccd5500bb23","contributors":{"authors":[{"text":"Eganhouse, Robert P. eganhous@usgs.gov","contributorId":2031,"corporation":false,"usgs":true,"family":"Eganhouse","given":"Robert P.","email":"eganhous@usgs.gov","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":680342,"contributorType":{"id":1,"text":"Authors"},"rank":1}]}} ]}